Principal Recruiter
Data Platform & Architecture
View profileAs the use of data in business gets more and more prevalent the ability to quickly and effectively produce data algorithms that can analyse large complex datasets is crucial. In order to do this, the right data infrastructure needs to be in place.
Why consider a career in Big Data?
Data Engineers build databases, data warehouses and data lakes to service the needs of the Data Analysts and Data Scientists in their businesses. This area is fast growing and Data Engineers are in massive demand as so many companies race to unlock the value in their data.
Typical role titles include
Data Engineer
Big Data Engineer
Data Developer
BI Engineer
BI Developer
Business Intelligence Developer
Business Intelligence Engineer
Big Data Developer
Hadoop Developer
Data factory Developer
Hadoop Engineer
Data Availability Engineer
Data Science Engineer
Big Data Software Engineer
Platform Engineer
Data Warehouse Engineer
DWH Engineer
DWH Programmer
DWH Developer
Datawarehouse Developer
Datawarehouse Engineer
Datawarehouse Programmer
SQL Server Engineer
Data Infrastructure Engineer
Data Infrastructure Programmer
Data Infrastructure Developer
Data Analytics Engineer
Big Data Architect
Hadoop Architect
Hadoop Specialist
Big Data Specialist
Big Data Lead
Head of Big Data
Data Architecture specialist
Head of Data Architecture
Career progression example
Junior Data Engineer
Data Engineer
Senior Data Engineer
Lead Data Engineer
Head of Data Engineering
Data Architect
Salary Benchmarks
We’ve outlined the latest salary benchmarks for Big Data roles in the guides below:
Data, Insight and Analytics Salary Guide
Data, Insight and Analytics Within Data Engineering Development Salary Guide
Data, Insight and Analytics Within Data Science Salary Guide
Is it right for me? The skills it takes…
The skills needed can be split into 3 categories; programming skills, data science understanding and problem-solving.
Programming skills: Java | Python | Golang | Cython | Software Design – A background in APIs e.g. web APIs and static/dynamic libraries | ML Libraries – e.g. TensorFlow, CNTK, MLib, Spark, Kafka, Kinesis, Redshift.
What qualifications does it take?
A BSc, Masters (MSc) or Doctorate (PhD) in a maths, physics, statistics, artificial intelligence (AI), software engineering, engineering or computer science field with technical skills in programming. Demonstrable experience working with large data sets or alternatively candidates will work in Business Intelligence and then do online courses /self-learning/ get trained up on Big Data Engineering and Architecture and can move into these roles through this route.
We connect ambitious organisations with their greatest assets, equally ambitious talent.
Potential to extend.
Remote work (from the UK).
Full details
09th Dec
Working with a recruitment partner like ADLIB means you’re working with a group of people who get to understand you and match candidates up with your culture and goals. ADLIB worked at a breakneck speed to introduce us to the marketing experts we needed to build our team in a matter of months. With their help we recruited and onboarded a new team much faster than planned and ended up spoilt for choice because of the way they work and market insights.
“From finding me my current role to helping place two fantastic hires, ADLIB has been a pivotal role in the development of our team here at Bristol. The guys are easy to work with, friendly and most importantly inspire trust. I look forward to working with them in the future.”
Average salaries and day rates typically received for Data, Insight and Analytics roles.
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Average salaries and day rates typically received for Data, Insight and Analytics roles.
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Average salaries and day rates for roles within data engineering & development.
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Average salaries and day rates typically received for Data, Insight and Analytics roles within Data Science.
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